WHO DEVIATES? TECHNOLOGICAL OPPORTUNITIES, CAREER CONCERN, AND INVENTOR'S DISTANT SEARCH

2021 ◽  
Author(s):  
Vivek Tandon ◽  
Puay Khoon (PK) Toh
Keyword(s):  
Career Concern ◽  
Technological Opportunities

Overachieving and Obsessive Behavior as Signaling Devices under Career Concern

2020 ◽  
Author(s):  
Alexander Rodivilov ◽  
Dongsoo Shin ◽  
Xiaojian Zhao
Keyword(s):  
Career Concern

scholarly journals Responsible Urban Innovation with Local Government Artificial Intelligence (AI): A Conceptual Framework and Research Agenda

2021 ◽  
Vol 7 (1) ◽  
pp. 71
Author(s):  
Tan Yigitcanlar ◽  
Juan M. Corchado ◽  
Rashid Mehmood ◽  
Rita Yi Man Li ◽  
Karen Mossberger ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Local Government ◽  
Conceptual Framework ◽  
Research Agenda ◽  
Future Studies ◽  
Expert Team ◽  
Research Questions ◽  
Urban Problems ◽  
Technological Opportunities ◽  
Made In

The urbanization problems we face may be alleviated using innovative digital technology. However, employing these technologies entails the risk of creating new urban problems and/or intensifying the old ones instead of alleviating them. Hence, in a world with immense technological opportunities and at the same time enormous urbanization challenges, it is critical to adopt the principles of responsible urban innovation. These principles assure the delivery of the desired urban outcomes and futures. We contribute to the existing responsible urban innovation discourse by focusing on local government artificial intelligence (AI) systems, providing a literature and practice overview, and a conceptual framework. In this perspective paper, we advocate for the need for balancing the costs, benefits, risks and impacts of developing, adopting, deploying and managing local government AI systems in order to achieve responsible urban innovation. The statements made in this perspective paper are based on a thorough review of the literature, research, developments, trends and applications carefully selected and analyzed by an expert team of investigators. This study provides new insights, develops a conceptual framework and identifies prospective research questions by placing local government AI systems under the microscope through the lens of responsible urban innovation. The presented overview and framework, along with the identified issues and research agenda, offer scholars prospective lines of research and development; where the outcomes of these future studies will help urban policymakers, managers and planners to better understand the crucial role played by local government AI systems in ensuring the achievement of responsible outcomes.

scholarly journals Constructing Patent Maps Using Text Mining to Sustainably Detect Potential Technological Opportunities

2018 ◽  
Vol 10 (10) ◽  
pp. 3729 ◽  
Author(s):  
Hei Wang ◽  
Yung Chi ◽  
Ping Hsin
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Rapid Development ◽  
Word Sense Disambiguation ◽  
Current Method ◽  
Word Sense ◽  
Competitive Advantages ◽  
Patent Documents ◽  
Technological Opportunities

With the advent of the knowledge economy, firms often compete for intellectual property rights. Being the first to acquire high-potential patents can assist firms in achieving future competitive advantages. To identify patents capable of being developed, firms often search for a focus by using existing patent documents. Because of the rapid development of technology, the number of patent documents is immense. A prominent topic among current firms is how to use this large number of patent documents to discover new business opportunities while avoiding conflicts with existing patents. In the search for technological opportunities, a crucial task is to present results in the form of an easily understood visualization. Currently, natural language processing can help in achieving this goal. In natural language processing, word sense disambiguation (WSD) is the problem of determining which “sense” (meaning) of a word is activated in a given context. Given a word and its possible senses, as defined by a dictionary, we classify the occurrence of a word in context into one or more of its sense classes. The features of the context (such as neighboring words) provide evidence for these classifications. The current method for patent document analysis warrants improvement in areas, such as the analysis of many dimensions and the development of recommendation methods. This study proposes a visualization method that supports semantics, reduces the number of dimensions formed by terms, and can easily be understood by users. Since polysemous words occur frequently in patent documents, we also propose a WSD method to decrease the calculated degrees of distortion between terms. An analysis of outlier distributions is used to construct a patent map capable of distinguishing similar patents. During the development of new strategies, the constructed patent map can assist firms in understanding patent distributions in commercial areas, thereby preventing patent infringement caused by the development of similar technologies. Subsequently, technological opportunities can be recommended according to the patent map, aiding firms in assessing relevant patents in commercial areas early and sustainably achieving future competitive advantages.

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